



"""simple docstring"""






from typing import Any

import numpy as np






def 			snake_case_    ( A_   :						np.ndarray		):


       '''simple docstring'''





       return np.array_equal(A_,							matrix.conjugate().T		)






def 			snake_case_    ( A_   :						np.ndarray,							A_   :						np.ndarray		):


       '''simple docstring'''





       _lowerCamelCase		:							Any            =					v.conjugate().T
       _lowerCamelCase		:							List[Any]            =					v_star.dot(A_		)
       assert isinstance(A_,							np.ndarray		)
       return (v_star_dot.dot(A_		)) / (v_star.dot(A_		))






def 			snake_case_    ( ):


       '''simple docstring'''





       _lowerCamelCase		:							Dict            =					np.array([[2, 2 + 1j, 4], [2 - 1j, 3, 1j], [4, -1j, 1]]		)
       _lowerCamelCase		:							List[Any]            =					np.array([[1], [2], [3]]		)
       assert is_hermitian(A_		), F'''{a} is not hermitian.'''
       print(rayleigh_quotient(A_,							A_		)		)

       _lowerCamelCase		:							List[str]            =					np.array([[1, 2, 4], [2, 3, -1], [4, -1, 1]]		)
       assert is_hermitian(A_		), F'''{a} is not hermitian.'''
       assert rayleigh_quotient(A_,							A_		) == float(3		)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   tests()








"""simple docstring"""




from ....configuration_utils import PretrainedConfig
from ....utils import logging


lowerCAmelCase				:     Union[str, Any]					=				logging.get_logger(__name__)

lowerCAmelCase				:     Union[str, Any]					=				{
    """speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json""",
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}






class        __magic_name__				(			UpperCAmelCase__							):






				'''simple docstring'''
				__UpperCamelCase         =		"mctct"





				def __init__(			self						,					_a=8_065						,					_a=1_536						,					_a=36						,					_a=6_144						,					_a=4						,					_a=384						,					_a=920						,					_a=1e-5						,					_a=0.3						,					_a="relu"						,					_a=0.02						,					_a=0.3						,					_a=0.3						,					_a=1						,					_a=0						,					_a=2						,					_a=1						,					_a=0.3						,					_a=1						,					_a=(7,)						,					_a=(3,)						,					_a=80						,					_a=1						,					_a=None						,					_a="sum"						,					_a=False						,					**_a						,					):





							"""simple docstring"""
							super().__init__(**_a						,					pad_token_id=_a						,					bos_token_id=_a						,					eos_token_id=_a					)
							lowerCamelCase      =   vocab_size
							lowerCamelCase      =   hidden_size
							lowerCamelCase      =   num_hidden_layers
							lowerCamelCase      =   intermediate_size
							lowerCamelCase      =   num_attention_heads
							lowerCamelCase      =   attention_head_dim
							lowerCamelCase      =   max_position_embeddings
							lowerCamelCase      =   layer_norm_eps
							lowerCamelCase      =   layerdrop
							lowerCamelCase      =   hidden_act
							lowerCamelCase      =   initializer_range
							lowerCamelCase      =   hidden_dropout_prob
							lowerCamelCase      =   attention_probs_dropout_prob
							lowerCamelCase      =   pad_token_id
							lowerCamelCase      =   bos_token_id
							lowerCamelCase      =   eos_token_id
							lowerCamelCase      =   conv_glu_dim
							lowerCamelCase      =   conv_dropout
							lowerCamelCase      =   num_conv_layers
							lowerCamelCase      =   input_feat_per_channel
							lowerCamelCase      =   input_channels
							lowerCamelCase      =   conv_channels
							lowerCamelCase      =   ctc_loss_reduction
							lowerCamelCase      =   ctc_zero_infinity

							# prevents config testing fail with exporting to json
							lowerCamelCase      =   list(_a					)
							lowerCamelCase      =   list(_a					)

							if len(self.conv_kernel					) != self.num_conv_layers:
										raise ValueError(
										    """Configuration for convolutional module is incorrect. """
										    """It is required that `len(config.conv_kernel)` == `config.num_conv_layers` """
										    f'but is `len(config.conv_kernel) = {len(self.conv_kernel					)}`, '
										    f'`config.num_conv_layers = {self.num_conv_layers}`.'					)



